Creating visualizations of large data sets is a difficult problem since the process of rendering a significantly large number of data points on a screen or printer with limited resolution involves a significant reduction in the detail available.
There are many statistical methods that are used to reduce the data points displayed on data visualizations. These methods fail to provide a means for representing data more concisely and without losing the information required to return to the original presentation. These methods also fail to allow the users to easily change the resolution of a visualization without extensive use of processing resources. Thus, there is a need for more advanced visualization technology that uses techniques that will enable users to analyze data of significant volume and complexity at varying levels of resolution without materially losing information and without requiring significant processing each time a change in resolution is made.